The main goal of this short course is to introduce the concept of structural health monitoring (SHM) applied to bridges and special civil structures. Why bridges rather than just special structures? Because bridges are considered the main vulnerable civil structure in the last decades due to the number of structural failures observed around the world. Why SHM rather than SHM of bridges? Because most of the techniques and general procedures described are independent of the structure. Therefore, the techniques are first presented for general applications and then most of the examples are shown in the context of bridges. This manner, students can learn the general concept of SHM and apply it later on to almost any engineering structure.
- Pose the SHM in the context of a statistical pattern recognition paradigm.
- Understand the differences between quasi-static and dynamics monitoring.
- Overview of sensors and DAQ hardware for designing an optimum instrumentation scheme for SHM.
- Understand the applicability of finite element modeling and machine learning for data interpretation and damage identification.
- Understand the goal of SHM for civil structures, especially for bridges, with current limitations, grande challenges, and future trends.
Who should apply
The course is tailored towards graduate students and/or practicing engineers working full-time in public and private institutions or consultancy companies.
Knowledge, abilities and skills to be acquired
After successful completing of this course, students will be capable to:
- Describe the historical and current real-world applications of damage identification in the civil engineering field, especially in bridges;
- Conduct damage identification using vibration-based SHM;
- Evaluating critically the results of damage identification for quality control;
- Provide creative solutions for safety evaluation of critical bridges;
- Choose available commercial software for damage identification analysis.
Application Deadline: 06/01/2023
Session #1: 17/01/2023, 17-20h (Lisbon Time)
Session #2: 19/01/2023, 17-20h (Lisbon Time)
Session #3: 24/01/2023, 17-20h (Lisbon Time)
Session #4: 26/01/2023, 17-20h (Lisbon Time)